Sovereign AI & Workflow Automation

Services

Every service runs on private GPU infrastructure within your jurisdiction. No data leaves your perimeter. No third-party API dependencies.

01

RAG Pipelines

Retrieval-augmented generation on your own infrastructure. Your documents are chunked, embedded, and stored in a vector database you control. When a query comes in, relevant context is retrieved and fed to an LLM running on your GPUs — not a third-party API.

  • Document ingestion: PDF, DOCX, HTML, Markdown, email archives
  • Embedding models running locally (BGE-M3, GTE, or custom)
  • Vector stores: Qdrant, ChromaDB, pgvector — self-hosted
  • Reranking for precision (GTE Reranker, Cohere-compatible)
  • Full audit trail: every query, every retrieved chunk, every response

Typical Use Cases

  • Internal knowledge base Q&A
  • Regulatory document search
  • Customer support automation
  • Contract and legal analysis
  • Technical documentation assistant
02

LLM Inference

Run open-weight language models on your own GPU fleet. We deploy and manage the inference stack — model serving, routing, load balancing, and failover — so your applications get fast, reliable AI without any data leaving your environment.

  • Models: Qwen, Llama, Mistral, DeepSeek, Gemma — any open-weight model
  • Serving: vLLM, TGI, or Ollama — optimised for your hardware
  • Routing: LiteLLM-compatible API — drop-in replacement for OpenAI API
  • Multi-model: run different models for different tasks simultaneously
  • Scaling: from a single GPU to multi-node clusters

Why Not SaaS?

Every prompt sent to OpenAI, Anthropic, or Google is logged, stored, and potentially used for training. For regulated industries, classified data, or competitive intelligence — that is an unacceptable risk.

With private inference, your prompts never leave your network.

03

AI Agents

Autonomous agents that reason, use tools, and execute multi-step tasks — running entirely on your infrastructure. No commercial AI API dependencies. Full control over agent behaviour, memory, and tool access.

  • Multi-step reasoning with tool use and function calling
  • Persistent memory and conversation context
  • Integration with your internal systems via APIs and databases
  • Configurable guardrails and safety policies
  • Fully auditable: every decision, every tool call, every output

Agent Capabilities

  • Research and summarisation
  • Code generation and review
  • Data analysis and reporting
  • Document drafting and editing
  • Process automation with human-in-the-loop
04

Private GPU Clusters

NVIDIA GPU clusters deployed in your data centre or co-location facility. No shared tenancy, no noisy neighbours, no egress fees. Full CUDA stack with drivers, libraries, and tooling managed by us.

  • NVIDIA B200, H100, A100, and L40S
  • Single-node or multi-node NVLink/NVSwitch configurations
  • Optimised for inference, fine-tuning, or training workloads
  • Bare-metal or virtualised with GPU passthrough
  • Monitoring: GPU utilisation, memory, temperature, power draw

Hardware We Deploy

We work with your procurement or source hardware directly. No markup on GPUs — you own the hardware, we configure and manage the stack.

05

Confidential VMs

Intel TDX-based confidential computing with GPU passthrough. Your data is encrypted not just at rest and in transit, but in use — even the infrastructure operator cannot access the VM's memory.

  • Intel TDX Trust Domain Extensions for memory encryption
  • GPU passthrough into confidential VMs (NVIDIA B200/H100)
  • Hardware-based remote attestation — cryptographic proof of VM integrity
  • Secure boot chain from firmware to application
  • Ideal for classified workloads, medical data, financial processing

Why Confidential Computing?

Traditional encryption protects data at rest (disk) and in transit (network). Confidential VMs add the missing layer: protection during processing. Even a compromised hypervisor cannot read your data.

06

Model Fine-Tuning

Train domain-specific models on your own data using your own GPUs. LoRA and QLoRA fine-tuning keeps your training data within your environment while producing models that understand your domain deeply.

  • LoRA / QLoRA for parameter-efficient fine-tuning
  • Full fine-tuning for maximum quality when resources allow
  • Training data never leaves your environment
  • Evaluation pipelines to measure model quality
  • Model versioning and A/B deployment

When to Fine-Tune

  • Domain-specific terminology and knowledge
  • Consistent output format and style
  • Improved accuracy on your specific use case
  • Smaller, faster models that match larger model quality
07

Workflow Automation

Self-hosted workflow automation connecting your systems — data ingestion, document processing, scheduled tasks, API integrations, and AI-powered pipelines. All running on your infrastructure.

  • n8n-based workflow engine — self-hosted, no SaaS dependency
  • 500+ integration nodes: databases, APIs, file systems, messaging
  • AI-powered workflows: LLM calls, embeddings, classification
  • Scheduled pipelines with retry logic and error handling
  • Webhook triggers for real-time event processing

Example Workflows

  • Document intake → OCR → classification → routing
  • Email monitoring → extraction → database update
  • Scheduled report generation with LLM summaries
  • API polling → data transformation → alerting
08

Web Intelligence

Self-hosted search and web scraping infrastructure. Gather competitive intelligence, monitor regulatory changes, or build research datasets — without sending your queries through third-party services.

  • Private meta-search engine — aggregate results without tracking
  • Structured web scraping with anti-detection capabilities
  • Stealth browsing infrastructure for JavaScript-rendered content
  • Scheduled monitoring and change detection
  • Integration with RAG pipelines for automatic knowledge base updates

Why Self-Hosted Search?

Every search query reveals intent. Using commercial search APIs tells a third party exactly what your organisation is researching. Self-hosted search keeps your intelligence gathering private.

09

Data Ingestion

Ingest from any source — databases, APIs, file stores, streaming platforms — normalise and enrich within your perimeter. Build unified data layers that feed your AI pipelines and analytics.

  • Connectors for SQL, NoSQL, REST APIs, S3, SFTP, and streaming
  • Schema-on-read or schema-on-write depending on use case
  • Data quality validation and anomaly detection
  • Incremental ingestion with change data capture
  • Metadata cataloguing and lineage tracking

Data Sources We Connect

  • Enterprise databases (PostgreSQL, Oracle, SQL Server)
  • Document stores (SharePoint, Confluence, file shares)
  • APIs and webhooks
  • Email and messaging platforms
  • IoT and sensor data streams

Ready to Deploy Sovereign AI?

Tell us about your workload and infrastructure requirements. We'll design a solution that keeps your data where it belongs.

Get in Touch